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docs: remove duplicated word 'in' in forcats content (#10331)
Co-authored-by: Lichao Chen <3780722+chenlichao@users.noreply.github.com>
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Lichao Chen
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# forcats
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forcats provides tools for working with factors, R's data type for categorical variables, making common tasks like reordering levels or lumping rare categories together more straightforward than base R. Functions like `fct_reorder()` let you control the order categories appear in in plots and tables, which matters since default factor ordering is often alphabetical rather than meaningful. It's especially useful when preparing categorical data for visualization.
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forcats provides tools for working with factors, R's data type for categorical variables, making common tasks like reordering levels or lumping rare categories together more straightforward than base R. Functions like `fct_reorder()` let you control the order categories appear in plots and tables, which matters since default factor ordering is often alphabetical rather than meaningful. It's especially useful when preparing categorical data for visualization.
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Visit the following resources to learn more:
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@@ -1,6 +1,6 @@
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# forcats
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forcats provides tools for working with factors, R's data type for categorical variables, making common tasks like reordering levels or lumping rare categories together more straightforward than base R. Functions like `fct_reorder()` let you control the order categories appear in in plots and tables, which matters since default factor ordering is often alphabetical rather than meaningful. It's especially useful when preparing categorical data for visualization.
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forcats provides tools for working with factors, R's data type for categorical variables, making common tasks like reordering levels or lumping rare categories together more straightforward than base R. Functions like `fct_reorder()` let you control the order categories appear in plots and tables, which matters since default factor ordering is often alphabetical rather than meaningful. It's especially useful when preparing categorical data for visualization.
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Visit the following resources to learn more:
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